Application of random constructive heuristics algorithm and tabu search on 3-dimensional container loading problem

Abstract

It is undeniable that finding the best logistics solutions for customers is the main task of a service provider, and this is never an easy thing. These solutions must be ideal and optimal in terms of workload, cost, time, and other resources. This directly upgrades and adds value to a company's supply chain. As a result, today's logistics organizations are always learning, developing, and implementing new technology to add value to their businesses. Maximizing container volume utilization is considered paramount for any business providing logistics services. Optimizing the capacity of containers not only helps to rationally use logistics resources, saving time and money, but also contributes to the sustainability of a business in this forever growing Logistics industry. However, many existing solutions to the problem of container handling (CLP), there are still trade-offs in each approach. Each person has their own characteristics, functions and qualities, so it is necessary to carefully consider each specific case. This thesis will illustrate on a hybrid approach to maximize container’s volume utilization, in the mean time still satisfy other important constraints such as weight limit, cargo’s stability, weight central distribution, … This thesis aims to apply Random Constructive Heuristics Algorithm and Tabu Search into solving the container loading problem. And then compare the results with other published studies.